The CARD trial was conducted in patients with metastatic castration-resistant prostate cancer (mCRPC) who had received docetaxel and experienced disease progression within 1 year on an androgen receptor-axis-targeted therapy (ARAT). Subsequent treatment with cabazitaxel had improved clinical outcomes compared with an alternative ARAT. This study aims to confirm the effectiveness of cabazitaxel in real-world patients in Japan and compare their characteristics with those of patients from the CARD trial.This was a post-hoc analysis of a nationwide post-marketing surveillance registering all patients who were prescribed cabazitaxel in Japan between September 2014 and June 2015. Included patients had received docetaxel and ≤ 1 year of an ARAT  prior to receiving cabazitaxel or an alternative ARAT, as their third-line therapy. The primary effectiveness endpoint was the time to treatment failure (TTF) of the third-line therapy. Patients were matched (1:1) from the cabazitaxel and second ARAT arms based on propensity score (PS).n = 263/288) received abiraterone and 8.7% (n = 25/288) received enzalutamide as their second third-line ARAT. Patients in the cabazitaxel and second ARAT arms had TNM classification of M1 or MX in 73.3% and 68.1%, Gleason score of 8–10 in 78.5% and 79.2% and mean (standard deviation) serum PSA levels of 483 (1370) and 594 (1241) ng/mL, respectively. Initial cabazitaxel dose was ≤ 20 mg/m2 in 61.9% (n = 153/247) of the patients in the cabazitaxel arm. The median TTF  of the third-line therapy was 109 (94–128) days for cabazitaxel and 58 (57–66) days for the second ARAT, with a hazard ratio (95% CI) of 0.339 (0.279–0.413) favouring cabazitaxel. Similar results were obtained after PS-matching, with a hazard ratio (95% CI) of 0.323 (95% CI 0.258–0.402) favouring cabazitaxel.Of the 535 patients analysed, 247 received cabazitaxel and 288 the alternative ARAT as their third-line therapy, of which, 91.3% (Consistent with the CARD trial, cabazitaxel demonstrated superior effectiveness over a second alternative ARAT in a real-world patient population in Japan, despite the population having more advanced disease status and a lower dose of cabazitaxel being more frequently administered, than in the CARD trial.The online version contains supplementary material available at 10.1186/s12885-023-10998-w. Prostate cancer (PC) is one of the most common types of cancer among men; age-standardized rate of PC worldwide was 30.7 per 100,000 person-years in 2020  days) and second ARAT (98 [89–100] days) arms Table : Fig. S1In the unmatched CARD-like cohort, median (95% CI) OS of the cabazitaxel arm was 326 (267– not estimable) days Fig. .Fig. 4KaReal-world evidence has been gaining regulatory acceptance as drug discovery, development, and translation evolves . New appP = 0.008) compared with the alternative ARAT [In the CARD clinical study, the frequency of adverse events (AEs) was similar between the cabazitaxel and the second alternative ARAT arms, though AEs leading to treatment discontinuation were reported more frequently with cabazitaxel . Cabazitive ARAT . Furtherive ARAT .2) was more frequently used in this study than in the CARD trial  [In this PMS study, the TTF of the third-line therapy for patients receiving an alternative ARAT was half of that for patients receiving cabazitaxel . Whereas imaging-based PFS was assessed as the primary endpoint in the CARD trial, TTF is generally considered to be more appropriate as a measure of effectiveness in clinical practice, because patients may discontinue therapies due to toxicity despite lack of disease progression, in daily practice. The median TTF of cabazitaxel in this study was 109 days and the median PFS in the CARD trial was 4.4 months . There actively) . Furtherctively) , which mctively) .The CARD trial enrolled patients who progressed within 1 year on the first ARAT . We emphABCB1 [Molecular mechanisms of cross-resistance between ARAT treatments include androgen receptor (AR) splice variants, AR overexpression, AR mutations, and glucocorticoid upregulation . Cell-baABCB1 . SimilarABCB1 . ProspecABCB1 . In the In this analysis, more than half of the CARD-like cohort received sequential ARAT, consistent with recent global real-world studies showing frequent sequential use of ARAT , 10. Ourpost-hoc analysis of a Japanese PMS of cabazitaxel, patient characteristics were collected at the start of cabazitaxel treatment; therefore, baseline characteristics before the third-line treatment were unknown for patients in the second ARAT arm (because they received cabazitaxel as a fourth- or fifth-line treatment). Whereas the proportions of patients receiving abiraterone and enzalutamide as a second ARAT were balanced in the CARD trial , the majority of the patients in our study received enzalutamide followed by abiraterone (91.3%), which may not have been the optimal sequencing of the two drugs [Care is needed when interpreting the effectiveness results of this study, which was an observational, non-blinded, non-randomized, non-controlled study design, which lends inherent risks for bias. A surrogate measure of effectiveness (TTF) was used in this study instead of using the same measure of efficacy as the CARD trial (imaging-based PFS). In this The study analysed data collected between September 2014 and June 2015. Since then, the prescribing landscape has changed with a trend toward using ARATs in the first line of treatment of mCSPC , as wellConsistent with the CARD trial, cabazitaxel demonstrated superior effectiveness over a second alternative ARAT in a real-world patient population in Japan, despite the population having more advanced disease status and a lower dose of cabazitaxel being more frequently administered, than in the CARD trial. Cross-resistance between the first ARAT and the second alternative ARAT was evident.Additional file 1: Table S1. Exposure to cabazitaxel, PSA response, and reasons for treatment discontinuation in the CARD-like cohort (cabazitaxel arm). Table S2. ADRs in the CARD-like cohort (cabazitaxel arm).Additional file 2: Fig. S1. Kaplan–Meier curves for time to treatment failure of the first ARAT (received as first or second line of treatment). ARAT androgen receptor axis-targeted agent. Fig. S2. Kaplan–Meier curves for time to treatment failure of abiraterone and enzalutamide as the first ARAT (a) or second alternative ARAT (b).


Enterococcus faecium, a common resident of the human gastrointestinal tract, is also a major pathogen. Prompt initiation of appropriate treatment is essential to improve patient outcome in disseminated E. faecium infections. However, ampicillin resistance is frequent in this species, rendering treatment difficult. We used a comprehensive approach, including clinical data review, whole-genome sequencing, and mass spectrometry, to characterize ampicillin-susceptible (EFM-S) and ampicillin-resistant (EFM-R) isolates. We included all patients with culture-confirmed E. faecium infection attending our hospital over a 16-month period. A comparison of 32 patients infected with EFM-S strains and 251 patients infected with EFM-R strains revealed that EFM-R isolates were strongly associated with a longer hospital stay, history of prior hospitalization, and the carriage of multidrug-resistant organisms. An analysis of the genomes of 26 EFM-S and 26 EFM-R isolates from paired patients revealed a population structure almost perfectly matching ampicillin susceptibility, with resistant isolates in clade A1, and susceptible isolates in clades A2 and B. The clade B and A2 isolates mostly came from digestive or biliary tract samples, whereas clade A1 isolates were mostly obtained from urine and blood. Finally, we built a custom database for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), which differentiated between clade B and clade A1/A2 strains with high-positive and high-negative predictive values . This study provides important new insight into the clinical features and clades associated with EFM-S and EFM-R isolates. In combination with MALDI-TOF MS, these data could facilitate the rapid initiation of the most appropriate treatment.Enterococcus faecium is an important human pathogen in which the prevalence of ampicillin resistance is high. However, little is known about the clinical characteristics of patients infected with ampicillin-resistant and ampicillin-susceptible strains. Indeed, current knowledge is based on genus-wide studies of Enterococcus or studies of very small numbers of susceptible isolates, precluding robust conclusions. Our data highlight specific clinical features related to the epidemiology of EFM-S and EFM-R strains, such as length of hospital stay, history of prior hospitalization, carriage of multidrug-resistant organisms, and type of sample from which the isolate was obtained. The use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with a custom-built database may make it possible to distinguish clade B isolates, which are typically susceptible to ampicillin, from clade A1/A2 isolates , thereby facilitating the management of these infections. Enterococcus faecalis and Enterococcus faecium, are the most prevalent species in humans. They are closely associated with the human intestinal microbiota and may cause a wide range of infections , is closely associated with the ampicillin-resistant strains of the A1 clade, and sometimes of the A2 clade, and is not observed in the ampicillin-susceptible strains of clade B    must be E. faecium from infected patients and to determine whether susceptibility could be predicted from the precise identification of E. faecium to clade level by MALDI-TOF mass spectrometry as part of the routine bacterial identification protocol.The objective of this study was to identify the risk factors associated with the isolation of ampicillin-susceptible (EFM-S) or -resistant (EFM-R) E. faecium infection tested for ampicillin susceptibility between 1 January 2020 and 20 April 2021 at the Bacteriology Unit of Henri Mondor Hospital , a 2,814-bed tertiary-care hospital. Isolates obtained during screening for vancomycin-resistant E. faecium (VRE) carriage were excluded. During the study period, bacterial identification was routinely performed with MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry), with the MALDI Biotyper system (Bruker). Ampicillin susceptibility was determined by the disk diffusion method, with a disk loaded with 2 µg of ampicillin, or by the broth microdilution method . The isolates were classified as susceptible or resistant to ampicillin according to CA-SFM  recommendations based on EUCAST  guidelines.We retrospectively included all patients with a documented We first focused on the clinical characteristics of the patients infected with EFM-S or EFM-R isolates. We took into account only the first episode for each patient included. We reviewed the demographic and clinical data for the patients with electronic medical records and a standardized form . The datWe then compared the sources of isolates and the polymicrobial nature of the infection as a function of ampicillin susceptibility. In this context, we included all isolates from all episodes occurring in all patients over the study period. Only redundant isolates obtained from the same clinical sample during a given episode were excluded. We encountered no cases of differences in susceptibility between isolates collected from the same source during the same episode.n = 26) identified over the survey period were thawed and paired with EFM-R isolates (n = 26) from patients of the same sex and similar age. The identification obtained with the MALDI-TOF MS Biotyper system (Bruker) and ampicillin susceptibility (disk diffusion method) was checked for all these isolates by the broth microdilution method (see above). The isolates were then subjected to whole-genome sequencing on an Illumina NextSeq sequencer (paired-end 150 bp reads).All available EFM-S isolates  using the taxonomy-specific workflow (species “E. faecium”) to ensure a completeness exceeding 95% and less than 5% contamination. Multi-locus sequence typing (MLST) was performed with mlst , A2 (n = 10), and B (n = 7) were selected for the construction of a custom-built MALDI-TOF MS database with MBT Compass RUO v4.1, FlexAnalysis v3.4, MBT compass explorer v4.1, and the MALDI Biotyper (Bruker). Proteins were extracted with the Mass Spectrum Profile (MSP) Creation protocol . Briefly, we collected fresh colonies with a 1-µL inoculation loop and mixed them with 300 µL LC-MS water. We then denatured the proteins by adding 900 µL pure ethanol. After careful vortexing and centrifugation , we discarded the supernatant and performed another centrifugation to remove the residual ethanol. The pellets were then dried at room temperature and were dissolved and thoroughly mixed in 30 µL each of 70% formic acid and acetonitrile. This solution was then centrifuged at 13,000 × g for 2 min. Finally, we spotted 1 µL of the supernatant onto an MSP 96 target BC steel plate for each of the eight replicates. We allowed the spots to dry and then coated the plate with 1 µL HCCA matrix solution . Mass spectra were obtained according to the MALDI Biotyper protocol  and were carefully inspected with FlexAnalysis software. Spectra with a mass peak deviation >0.05%, outlier peaks, and flatlines were eliminated, and the remaining spectra were combined to generate a single mass spectrum for each strain in MBT compass explorer, with the default parameters. The mass spectra were used to generate a new local database, available from the MALDI Biotyper Compass RUO software. We also constructed a dendrogram from these MSPs on the MALDI Biotyper Compass RUO  to check the clustering of isolates.Based on the susceptibility testing results and the whole-genome sequencing analysis, 10 EFM-R and 17 EFM-S isolates corresponding to clades A1 . For an identification to be considered valid, it had to meet the following criteria: a log score ≥2.0 and concordance of the first two identification scores for ampicillin susceptibility and clade membership. Positive and negative predictive values were calculated for each of these parameters separately.U tests. A P-value <0.05 was considered statistically significant.Statistical analyses were performed with GraphPad Prism v.5. and Stata v.16.0. Categorical variables are expressed as numbers  and were compared in Fisher’s exact tests. Continuous variables are expressed as medians  and were compared in Mann-Whitney P-value in the univariate analysis was >0.15. We used the Wald test for systematic evaluations of the interactions between each of the variables in the final model. Collinear variables were excluded from the multivariate analysis. The number of relevant variables reported in the final multivariate model was adapted to the number of events to calculate odds ratios (1 variable: 10 patients).Logistic regression analysis was performed to identify the factors independently associated with EFM-S isolates. We excluded variables from the multivariate analysis if their n = 32) or EFM-R (n = 251) are shown in P = 0.02). Patients with EFM-S were more frequently hospitalized in digestive surgery units . Those with EFM-R were hospitalized for a longer period , were more likely to have a history of prior hospitalization during the preceding year , and were more frequently MDRO carriers . Moreover, EFM-R patients were more likely to suffer from hemopathy  and require intensive care .The demographic and clinical characteristics of the 283 patients infected with EFM-S , 19 involved isolates from the same source (n = 41 isolates), and 7 episodes involved isolates from both the same and different sources (n = 27 isolates).Overall, 372 isolates of n = 27/38; 71.1% vs 15.0% n = 50/334 for EFM-R isolates; P < 0.0001). EFM-S isolates were more frequently obtained from biliary samples , peritoneal fluid , and abdominal mass  than EFM-R isolates. They were also more frequently obtained from polymicrobial cultures . Conversely, EFM-R isolates were more frequently obtained from blood cultures  and urinary samples  than EFM-S isolates. Vancomycin resistance was detected in only two EFM-R isolates and none of the EFM-S isolates.In total, 38 isolates (10.2%) were ampicillin susceptible, and 334 (89.8%) were ampicillin resistant. Most of the EFM-S isolates were isolated from digestive samples . We paired these 26 EFM-S isolates with 26 EFM-R isolates from patients of the same age and sex. All these isolates were then sequenced with Illumina short-read technology and analyzed. Core genome phylogenetic analysis of these genomes and those from the data set of Lebreton et al. . Finally, the resistant strains of the A2 clade displayed at least two characteristics of the non-A pattern, the insertion at position 466′ and the mutation at position 485. The only exception was the EnGen0052 genome. However, Montealegre et al. had already noted a discrepancy for this strain (n = 15) and corresponds to a shortened msr gene (597 bp) with no ftsW upstream. Pattern G was also found only in clade A1 (n = 8) and consists of a reduced msr gene (642 bp) with an upstream ISEfm1. Pattern H, found in the A2 (n = 6) and A1 (n = 1) clades, was similar to pattern B but with no insertion sequence between msr and pbp5. Finally, pattern I was also similar to pattern B but with an IS1542 instead of an ISEfm1.In total, 52 isolates were selected for further analysis, including the 26 isolates available from the 38 EFM-S isolates identified over the survey period. The remaining 12 EFM-S strains were not available due to the short shelf-life of isolates for some samples  or blood cultures (n = 6/27), and these isolates frequently belonged to ST80 (n = 8/27) and ST117 (n = 11/27). Conversely, the isolates of clades B and A2 were mostly isolated from digestive or biliary tract-related samples  and were more diverse in terms of ST . The dendrogram constructed from the MSPs showed that isolates from clade B clustered on one side and those from clades A1/A2 clustered on the other . The individual spectra and the database generated from them are publicly available from Zenodo  appeared very low. However, performances were much better for distinguishing clade B from clade A1/A2, with very high-positive and -negative predictive values .Enterococcus spp. . We first show that the patients with infections involving EFM-R can be clearly distinguished from those with infections involving EFM-S by the significantly longer hospital stay, more frequent history of hospitalization within the preceding year, and more frequent MDRO carriage in patients with EFM-R isolates, highlighting the link to the nosocomial environment. The association between ampicillin resistance and the hospital environment has already been established in cus spp. , 32, butE. faecium population is organized into a limited number of clades—A1, A2, and B—highly congruent with the community or hospital origin of the isolates  system, using a subset of 27 isolates, and we evaluated its performance on 52 isolates. The proximity of the sister clades A1 and A2 made it impossible to discriminate between them. Consequently, we were also unable to distinguish between isolates on the basis of ampicillin susceptibility profile at the whole-population scale. Nevertheless, this database performed well for discriminating clade B isolates from those of clades A1/A2. These results were expected, given the significant genetic divergence of clade B from clades A1/A2, suggesting that they could almost be considered to belong to two different species , 35. HowEnterococcus infections  straight away. Indeed, some studies have suggested that the use of vancomycin rather than ampicillin may lead to a poorer outcome in ampicillin-sensitive fections , 13. FurE. faecium species. The lower frequency of EFM-S (10.2% here) isolates reported here may account for the lack of published data.Our study has several limitations, including its retrospective, single-center nature. Larger prospective studies, including more diverse hospitals and patients, will be required to confirm our results. Future studies should also try to decipher and confirm the clinical characteristics of patients associated with each clade through robust statistical tests. In addition, the inclusion of a larger number of isolates would make it possible to improve the MALDI-TOF database, to prevent discrepancies due to a divergent isolate from clade B. Nevertheless, the results obtained are consistent with the known ampicillin susceptibility profiles and clades of the isolates. Moreover, to the best of our knowledge, this is one of the few studies focusing solely on the In conclusion, we think that combining clinical data with bacterial identification via our custom-built MALDI-TOF MS database would make it easier to distinguish between EFM-S and EFM-R isolates. MALDI-TOF MS is widely available for bacterial identification in clinical bacteriology laboratories. Our database could, therefore, be incorporated into routine use, facilitating early initiation of the most appropriate treatment. The early use of a narrow-spectrum antibiotic, such as ampicillin instead of glycopeptides, would prevent exposure to broad-spectrum antibiotics even for as little as 24 or 48 hours, which is known to increase the risk of acquiring multidrug-resistant bacteria.


A logistic regression model was used to determine the independent risk factors for mortality. Machine learning models were used to analyze the contribution of independent variables to the mortality in LT recipients. Results: The COVID-19-related mortality rate in LT recipients was 7.2%. Multivariate analysis showed that everolimus use , need for intubation  and discontinuation of immunosuppressive therapy  were independent risk factors for mortality. Furthermore, COVID-19 vaccination reduced the risk of mortality by 100 fold and was the single independent factor determining the survival of the LT recipients. Conclusion: The effect of COVID-19 infection on LT recipients is slightly different from the effect of the disease on the general population. The COVID-19-related mortality is lower than the general population and vaccination for COVID-19 significantly reduces the risk of mortality.Background: In liver transplant (LT) recipients, immunosuppressive therapy may potentially increase the risk of severe COVID-19 and may increase the mortality in patients. However, studies have shown conflicting results, with various studies reporting poor outcomes while the others show no difference between the LT recipients and healthy population. The aim of this study is to determine the impact of the COVID-19 pandemic on survival of LT recipients. Methods: This is a retrospective cohort study analyzing the data from 387 LT recipients diagnosed with COVID-19. LT recipients were divided into two groups: survival ( In December 2019, an outbreak of acute and highly lethal atypical pneumonia was observed in the Wuhan city of Hubei Province of China. It was later shown that this disease was a viral pneumonia caused by a novel coronavirus severe acute respiratory syndrome associated Corona Virus-2 (SARS-CoV-2). The disease was renamed as Coronavirus Infectious Disease-2019 (COVID-19) ,4,5. A mIn the initial stages of the pandemic, it was hypothesized that liver transplant (LT) recipients were at higher risk of mortality due to COVID-19 because of the immunosuppressive therapy and concomitant co-morbid diseases ,12,13,14One of the concerns in LT recipients with COVID-19 is graft loss. There are two possible mechanisms for graft loss during COVID-19. First one is the direct cytopathic effect of the virus in hepatocytes due to upregulation of the ACE-2 receptors in the liver during regeneration, so the liver graft may especially be prone to infection with the virus ,16. The Our center has an annual LDLT volume of 250 to 300 cases. Furthermore, we have a recipient pool of more than 3000 individuals operated since the initiation of the transplant program in 2002. The main objective of this cohort study is to determine the demographic and clinical factors affecting mortality among LT recipients with COVID-19 infection.Between March 2002 and November 2021, more than 3000 LT recipients underwent LT for various etiologies in our institute, but 1882 LT recipients who had sufficient data were analyzed for this retrospective cohort study. In addition, the data of the LT recipients who died during the COVID-19 period were also retrospectively analyzed.The following demographic and clinical characteristics were included in this cohort study: age, gender, height, weight, blood groups, marital status, occupation, level of education, comorbidity , smoking, immunosuppressive drugs , type of LT , retransplantation (reLT), diagnostic tools for COVID-19, lung involvement, antiviral drugs used for COVID-19, hospitalization, intensive care unit (ICU) stay, intubation status, COVID-19 vaccination, signs and symptoms related with COVID-19, awareness about COVID-19 and vaccination, white blood cell count (WBC), lymphocyte count, neutrophil count, platelet counts, aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBil), C-reactive protein (CRP), hemoglobin (Hb), mean platelet volume (MPV), alteration of the course of immunosuppressive medication  and patient outcomes . We have classified mortality as COVID-19-associated mortality which implies acute respiratory distress associated with the early phases of the disease (≤2 weeks). COVID-19 related mortality is defined as patient mortality related with cytokine storm and multiple organ failure which resulted in mortality in the later phase of the disease (>2 weeks).This retrospective cohort study involving human participants was in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. First approval was obtained from the Ministry of Health of Turkey. Second approval was obtained from the Director of the Inonu University Liver Institute . Finally, ethics committee approval was obtained from the Inonu University institutional review board (IRB) for non-interventional clinical research .After the initial evaluation of physical signs and symptoms, the patients who were suspected to have COVID-19 were managed according to guidelines prepared by the Scientific Board of the Ministry of Health of Turkey. Reverse-transcription polymerase chain reaction (RT-PCR) test was performed by analyzing the nasopharyngeal and oropharyngeal swab samples. Thoracic computerized tomography (CT) was performed in LT recipients with negative RT-PCR tests but who were suspected to have COVID-19 pneumonia. Also, the thorax CT was performed in RT-PCR positive LT recipients to evaluate the extent of lung involvement in PCR positive patients. In patients with persistent clinical suspicion but negative PCR, the test was repeated 24–48 h after the previous test. The LT recipients diagnosed with COVID-19 were admitted to the clinics or intensive care units that were reserved for patients with COVID-19. These LT recipients were managed by multidisciplinary team according to the guidelines of the Ministry Health of Turkey. The data of the LT recipients treated in other centers were accessed both through the hospital information system and by telephone interview. We could not reach the laboratory values of 146 LT recipients that were treated elsewhere.p values in chi-square tests were obtained by univariate logistic regression analysis. Variables with a significant p value in univariate analyzes were included in multivariate analysis using the backward method. Statistical tests with a p value of less than 5% were considered significant.Statistical analyses were performed using IBM SPSS Statistics for Windows version 26.0 . Categorical variables were expressed as number of affected individuals and percentage of the study population. Pearson’s chi-square test, continuity-corrected chi-square test or Fisher’s exact test were used where appropriate for the comparison of categorical variables. Missing values for quantitative variables were assigned according to the median. Quantitative variables were expressed as median (interquartile range). The continuous variables in the two groups were compared with the Mann–Whitney U test. In this study, in addition to baseline comparisons, effect sizes (ES) were calculated to evaluate the effects of each variable in the patients who were alive and dead. ES is defined as the size of the difference between groups. The interpretation of Cramer’s V coefficient used in calculating the ES for chi-square tests is interpreted differently according to the minimum number of categories (k) in the rows and columns. If k = 2, 0.10–0.30 is interpreted as a small effect, 0.30–0.50 as a medium effect, and above 0.50 as a large effect. If k = 3, it is interpreted as a small effect between 0.07–0.20, a medium effect between 0.20–0.35, and a large effect over 0.35 . For theA machine learning (ML) model was developed to predict all-cause mortality. At this stage, the LightGBM algorithm, which can process large-scale data with high accuracy and works based on histograms, was used . Since tStratified random sampling method was used to divide the obtained 426 samples into training and test sets at a ratio of 4:1. LASSO  feature Between March 2002 and November 2021, we performed about 3000 LT for various indications. Only 387 patients developed COVID-19 infections during the follow and they were included in the study.All the 387 LT recipients who were diagnosed with COVID-19 were included in the study. The median age of the patients was 53  years. In total, 111 (28.7%) patients were female and 276 (71.3%) were male. During the follow up period, 28 patients died due to COVID-19 infection. Of these, 14 of the patients died directly from the COVID-19 infection while the remaining 14 died from COVID-19 related complications. The median duration of survival of the patients who died from COVID-19 infection was 15.5 days (IQR: 20). The median survival period of the patients who died from COVID-19 related complications was 30.5 (IQR: 51) days. The median (95% CI) duration from LT procedure to COVID-19 of the patients who were on prednisolone was 10 months (6–20 months). On the other hand, the median (95% CI) interval between LT procedure and COVID-19 of the patients who are not on prednisolone was 60 months (53–72 months). The demographic and clinical characteristics of the LT recipients with COVID-19 are summarized in n = 359) and the patients that died from the COVID-19 infection (n = 28). Comparison of quantitative variables of the LT recipients is summarized in p = 0.085). Among the 28 mortalities observed, 4 were in pediatric patients and 24 adult patients, respectively. We observed an inverse relationship between the patients’ weight and mortality from COVID-19 infection with a p-value of 0.003. However, the ES showed that this difference among the patients’ weight was not clinically significant (Cohen’s d: 0.3). Other demographic parameters such as age (p = 0.168), height (p = 0.447), number of COVID-19 episodes (p = 0.413) and the duration between the initiation of symptoms and the diagnosis (p = 0.976) did not show significant differences between the two group of LT recipients.To analyze the risk factors affecting mortality, the LT recipients with COVID-19 infection were divided into two subgroups; patients who survived (p = 0.027), tacrolimus therapy (p = 0.015), everolimus therapy (p = 0.009) and prednisolone administration (p = 0.048). The ES value of reLT (Cramér’s V = 0.135), tacrolimus therapy (Cramér’s V = 0.138), everolimus therapy (Cramér’s V = 0.143) and prednisolone administration (Cramér’s V = 0.109) indicated that these parameters had some impact on the mortality of the patients. The results of the univariate analysis showed that StatreLT increased the mortality risk by 4.4 fold (95% CI = 1.3–14.6), everolimus therapy increased the mortality risk by 2.94 fold (95% CI = 1.35–6.42) and prednisolone administration increased the risk of mortality by 2.53 fold (95% CI = 1.01–6.06). On the other hand, tacrolimus therapy reduced the risk of mortality by 3.44 fold (95% CI = 1.35–8.33).A comparison of qualitative variables of the LT recipients is summarized in p = 0.102). In total, 8 patients who died due to COVID-19-related etiologies received a liver transplant ≤1 year; on the other hand, 20 patients who died related to COVID-19 etiologies received a liver transplant >1 year. As we have stated previously, a total of 304 patients received vaccination. There is no difference in mortality among patients who did and did not contract COVID-19 following vaccination (p = 1.0). However, the number of patients is low. A more striking result is that 24 patients who died due to COVID-19 related etiologies have expired before the era of vaccination.Furthermore, we have analyzed the LT cohort in terms of the interval between the LT procedure until contracting COVID-19. We have grouped the patients into two groups according to the time interval since LT (≤1 year versus 1 year) and no statistically significant difference was found between the groups in terms of mortality rates (p = 0.181) and C-reactive protein (p = 0.574) levels among the patients with and without mortality.We have tried to analyze the severity of inflammation among our patients by analyzing the Procalcitonin and C-reactive Protein levels of the patients and we not found a significant difference in terms of procalcitonin (p = 0.002), antiviral drugs use for COVID-19 (p = 0.027), hospitalization (p < 0.001), ICU stay (p < 0.001), need for intubation (p < 0.001), COVID-19 vaccination (p < 0.001), shortness of breath (p = 0.03) and alteration of immunosuppressive drugs during COVID-19 (p < 0.001). When we calculated the ES value, we found that the values for lung involvement (Cramér’s V = 0.169), antiviral drugs use (Cramér’s V = 0.123), hospitalization (Cramér’s V = 0.27) and shortness of breath (Cramér’s V = 0.122) were very small. On the other hand, the ES values for COVID-19 vaccination (Cramér’s V = 0.437) and alteration of immunosuppressive drugs during COVID-19 (Cramér’s V = 0.397) were moderately high ES values. This shows that COVID-19 vaccination and alteration of the immunosuppressive medications had higher clinical importance. ICU stay (Cramér’s V = 0.599) and need for intubation (Cramér’s V = 0.714) had the highest ES values and had the highest clinical significance. The univariate analyses of the variables in A comparison of qualitative variables regarding the COVID-19-related symptoms is summarized in p = 0.018; OR = 1.48). However, ES showed that the difference could be negligible (Cramér’s V = 0.146). There was no difference in terms of variables such as opinions regarding the protective capacity of the vaccine (p = 0.500), and the views of the LT recipients on the vaccine being legally obligatory (p = 0.500).p < 0.001), platelets (p = 0.013), Tbil (p < 0.001), Hb (p < 0.001) and MPV (p = 0.012). When we calculated the ES, we found that platelets (Cohen’s d = 0.323) and MPV (Cohen’s d = 0.328) had moderate or low ES values which precludes its clinical significance in terms of mortality. On the other hand, lymphocyte (Cohen’s d = 0.577) and Hb (Cohen’s d = 0.604) had higher ES values which indicates their importance in predicting mortality in clinical practice. TBil (Cohen’s d = 0.853) had the highest ES values which indicates that it has the highest impact in predicting mortality. Lymphocyte  and platelets , Tbil , Hb; OR = 1.00) and MPV  had significant correlations with the risk of mortality.p = 0.012; OR = 6.2), need for intubation  and discontinuation of immunosuppressive drugs  were significant and independent risk factors predicting mortality. Furthermore, COVID-19 vaccination reduced the risk of mortality by 100 fold and was the single independent factor determining the survival of the LT recipients.This study is unique because it is the only single-center, high-volume study evaluating the clinical features of COVID-19 in LT recipients. Furthermore, we evaluated multiple aspects of the disease including clinical characteristics, laboratory values, effect of immunosuppression therapy and vaccination in this highly specialized cohort.The outcomes of COVID-19 in LT recipients are not uniform. While some studies have reported increased mortality, other studies are reporting comparable or decreased mortality in comparison to the general population ,11,13,24There are studies evaluating the effects of different immunosuppressives on the immunogenicity of mRNA-based vaccines for SARS-CoV-2 ,35,36,37Lymphopenia was reported to be an independent risk factor in predicting mortality in patients with COVID-19 ,39. In oBilirubin has long been defined as a prognostic factor in patients with acute or chronic end-stage liver disease ,42,43,44Platelets have important functions in liver regeneration, and also the ischemia-reperfusion injury observed during LT and has been studied extensively in partial liver grafts ,50,51. IAdmission into the intensive care unit and intubation are associated with increased risk of mortality in patients with COVID-19 ,38,53,54The COVID-19 vaccines reduce the mortality of COVID-19 in solid organ transplant recipients by 2 to 8 fold ,57. FurtOne of the most important aspects of the current study is the use of artificial intelligence (AI) for development of a prognostic model for COVID-19 in LT recipients. The AI model determined total bilirubin, MPV, COVID-19 vaccination status, need for intubation, lymphocyte and platelet counts as potential factors determining the prognosis of the LT recipients with COVID-19. Machine learning in medical research enables evaluation of mass data and evaluation of complex medical problems where data is limited. It is an algorithm-based system that develops a predictable pattern in the guidance of the data regarding the research subject . TherefoThe present study is the first single center high volume study evaluating the outcome of COVID-19 in solid organ transplant recipients. The results are striking and delineates independent predictors of mortality among liver transplant recipients with COVID 19 infection, the efficacy of the vaccines in protection against COVID infection among recipients and we present a predictive model for determining the mortality in the patients. However, the present study has some limitations. The retrospective nature of the study precluded reaching necessary data in some of the patients. Furthermore, some of the recipients who had COVID-19 were diagnosed and treated in other centers and the laboratory parameters showed differences.The present study is designed as a retrospective cohort study. The results of retrospective studies are not as powerful as prospective cohort studies. Furthermore, we could not perform a matched cohort of non-transplanted patients which is another limitation. We could not select a matched cohort because data regarding the course of COVID-19 in the Turkish population is lacking. However, it is impossible to make prospective studies during a pandemic. The present study includes the data of our patients in the first two years of the pandemic. The patients in the last year of the study were not included, which is a very important limitation of our study. The majority of the patients lived in different parts of Turkey and in the beginning of the pandemic, the transportation between the centers were severely limited. For this reason, our patients with COVID-19 had to be treated in their cities of residence. The clinical approach of different physicians treating these patients severely limited the laboratory values obtained. Furthermore, the majority of the physicians struggling with the pandemic focused primarily on the clinical situation of the patients rather than the academic dimension of this catastrophe. Hence, we could not obtain many laboratory parameters for our patients and the parameters that were obtained were not uniform. Despite all these limitations, our study included a large volume of patients which we believe should increase the power of our results.In conclusion, LT recipients do not have an elevated risk of mortality related to COVID-19. Furthermore, risk factors for mortality are similar to non-transplanted population. Vaccines are extremely effective in reducing COVID-19-related mortality in solid organ transplant recipients. Globally, governments should take precautions to promote vaccination and to reduce vaccine opposition.


Studies associate chronic kidney disease (CKD) with neurodegeneration. This study investigated the relationship between kidney function, blood, CSF, and structural brain MRI markers of neurodegeneration in a sample including individuals with and without CKD.Participants from the Gothenburg H70 Birth Cohort Study, with data on plasma neurofilament light (P-NfL), estimated glomerular filtration rate (eGFR), and structural brain MRI were included. Participants were invited to also have the CSF collected. The primary endpoint of this study was to determine any association between CKD and P-NfL. Secondary endpoints included cross-sectional associations between CKD, eGFR, and CSF-derived and MRI-derived markers of neurodegeneration and Alzheimer disease (AD) pathology  42, Aβ42/40, Aβ42/p-tau, t-tau, p-tau, and NfL). Participants with P-NfL and eGFR at baseline were re-examined on eGFR, 5.5 (5.3–6.1) years  after the first visit, and the predictive value of P-NfL levels on incident CKD was estimated longitudinally, using a Cox proportional hazards model.p < 0.001), while MRI and CSF markers were similar between the groups. P-NfL was independently associated with CKD after adjustment for confounding variables, including hypertension and diabetes , in a logistic regression model. eGFR and CSF Aβ 42/40: R = 0.23, p = 0.004 correlated in participants with Aβ42 pathology. P-NfL levels in the highest quartile were associated with incident CKD at follow-up .We included 744 participants, 668 without CKD  and 76 with CKD . Biomarkers from the CSF were analyzed in 313 participants. A total of 558 individuals returned for a re-examination of eGFR . Participants with CKD had higher P-NfL levels than those with normal kidney function (median; 18.8 vs 14.1 pg/mL, In a community-based cohort of 70-year olds, P-NfL was associated with both prevalent and incident CKD, while CSF and/or imaging measures did not differ by CKD status. Participants with CKD and dementia presented similar levels of P-NfL. Some authors suggest that CKD and kidney function could alter a biomarkers' normal reference range and should be considered when used in clinical screening and diagnosis in cognitively healthy populations or in clinical studies of neurodegeneration.19CKD has previously been associated with blood-based biomarkers of neurodegeneration , and neurofilament light protein [NfL])21 P-NfL is also high in amyotrophic lateral sclerosis (ALS), atypical parkinsonian disorders, frontotemporal dementia, and in patients with Down syndrome with AD, providing evidence of an underlying neurodegenerative cause of a patient's symptoms.21-23Plasma neurofilament light protein (P-NfL) is a promising biomarker of neurodegeneration for use in a primary care setting because it is analyzed from blood and not CSF. P-NfL segregates depression from dementia in older individuals, and while only mildly elevated in patients with AD, it is an efficient marker for ruling out underlying neurodegeneration.9 However, studies specifically focused on the interaction between kidney function and different neurodegenerative markers in a community-based setting of older individuals with CKD and normal kidney function are currently few. The Alzheimer Association has specifically highlighted the need for studies on the influence of kidney disease on the diagnostic performance of P-NfL as one of the top research priorities in its recent statement paper on the use of blood-based biomarkers.24 The aim of this study was to investigate kidney function associations with P-NfL and several other markers of neurodegeneration in individuals with and without CKD.Studies on the influence of several comorbidities and different blood-based biomarkers have reported an influence of kidney function on P-NfL.25 with data available on P-NfL, estimated glomerular filtration rate (eGFR), and established structural MRI variables in studies of dementia, mean cortical thickness,26 mean lateral ventricle volume,26 mean hippocampal volume,26 and total white matter lesion volume27 (n = 744) (25 The primary endpoint of this study was to determine any association between CKD and P-NfL. Secondary endpoints included associations between CKD and other markers of neurodegeneration and any association between kidney function measured as eGFR and CSF-derived and MRI-derived markers of neurodegeneration.This study was conducted in participants from the Gothenburg H70 Birth Cohort 1944n = 744) . The cohBesides health interviews, blood sampling, and physical examinations, all participants who did not present with any contraindications were also invited to a brain MRI examination and a lumbar puncture. Due to the limited participation rate for CSF sampling, associations determined with CSF biomarkers were conducted as a substudy of participants with available CSF and complete data on fluid-based biomarkers of neurodegeneration (n = 313). Blood samples were collected at the first study visit, brain MRI was conducted within 3 months of the initial study visit, and lumbar puncture was performed within 2 months of the MRI examination.This study was conducted according to the Helsinki Declaration approved by the Regional Ethical Review Board in Gothenburg . All the participants and/or their close relatives gave written consent before any study-related procedures were performed.Anonymized data can be obtained by reasonable request from any qualified investigator.2), eGFR was calculated according to CKD-epi,28 using the formula mentioned further. CKD was defined as an eGFR below 60 mL/min/1.73 m2.29All participants attended a health examination at the Neuropsychiatric Clinic at Sahlgrenska University Hospital in Gothenburg, Sweden, conducted by the Gothenburg H70 Birth Cohort Study team. Participants underwent a health interview covering social and medical aspects. Anthropometric variables were determined, including weight, height, and blood pressure. BMI was calculated as weight (kg)/height  or 0.9 Alpha = -0.329  or -0.411 Medical comorbidities were determined through a combination of health interviews, data in the Swedish National In-patient register, and collected clinical variables. CDR was assessed by research nurses with specific training, and dementia was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition, revised criteria. CDR score and dementia diagnoses were also verified by study physicians in consensus conferences. Hypertension was defined as a systolic blood pressure >140 mm Hg, a diastolic blood pressure >90 mm Hg, or a history of hypertension with ongoing medication reported by the participant.A stroke was determined if the participant or a close relative reported the diagnosis, if it was diagnosed in the Swedish National In-patient register, or there were stroke-specific findings on the MRI scan. A history of transitory ischemic attacks was not classified as a stroke. Diabetes was defined as a previous diagnosis of diabetes or if the participant presented an fP-glucose ≥7.0 mmol/L at the study visit.Blood samples were collected in the morning after overnight fasting. Creatinine, fasting plasma glucose (fP-glucose), homocysteine, C-reactive protein, and LDL cholesterol were analyzed at the Sahlgrenska Clinical Chemistry laboratory. P-NfL was analyzed using the NF-Light kit on a Simoa HD-X Analyzer  at the Neurochemistry Laboratory at Sahlgrenska University Hospital, Mölndal, according to the manufacturer's instructions. Quality control samples presented a 7.6% repeatability and 8% intermediate precision (at 6.6 pg/mL) and a 7.2% repeatability and 7.8% intermediate precision (at 50.5 pg/mL).APOE genotyping with the KASPar PCR SNP genotyping system . APOE ε2, ε3, and ε4 alleles were defined by single-nucleotide variants rs7412 and rs429358 (n = 744).Blood was collected for 25 CSF samples were centrifuged, gently mixed, and stored at −80°C until analysis.Lumbar puncture was performed on a separate day by a medical doctor specialized in psychiatry or neurology.31 while INNOTEST Aβ1-42 was used to measure the 42-amino acid long version of Aβ (Aβ42).32 The V-PLEX Aβ Peptide Panel 1 (6E10) Kit  was used to measure the CSF Aβ42/40 ratio.33 Aβ pathology status was defined as Aβ42 levels below 530 pg/mL in accordance with a previously conducted longitudinal study predicting incident AD.34T-tau and p-tau in the CSF were analyzed using commercial enzyme-linked immunosorbent assays (ELISA) ,36 All assays are used in routine clinical analyses at the Mölndal Clinical Neurochemistry laboratory.37 Analytical runs passed quality control criteria for the calibrators, and internal quality control samples were approved as previously described in detail.37CSF NfL was measured with an ELISA developed at the Mölndal Clinical Neurochemistry Laboratory.25 The mean cortical thickness and mean lateral ventricular and hippocampal volumes were quantified using FreeSurfer 6.0.0 through the TheHiveDB,38 and the mean volume between the left and right sides was calculated for ventricles and hippocampus.6 Total white matter lesion volumes were measured using the open-source segmentation toolbox LST 2.0.15 implemented in the SPM software as previously described.39 All volumes were normalized by ratio to total intracranial volume, as previously described.6Brain MRI was conducted at the Aleris Clinic in Gothenburg using a 3.0T Philips Achieva system as previously described in detail.2.Participants in H70 Birth Cohort 1944 were invited for a re-examination after the age of 75 years. Individuals without CKD and with P-NfL and eGFR measured at baseline were included in the study for a longitudinal evaluation on incident CKD, defined as a follow-up eGFR < 60 mL/min/1.73 m2 or Fisher exact test as appropriate. For groupwise comparisons of continuous variables, the Mann-Whitney U test or Kruskal-Wallis test was used. Correlations were determined using Spearman correlations. For the cross-sectional logistic regression analysis with CKD as the dependent variable and P-NfL as the independent continuous variable, 3 models were constructed with age, sex, and years of education as covariates in model I. Model II included additional adjustments for medical history of hypertension or diabetes and model III with additional adjustments for smoking, BMI, fP-glucose, S-LDL cholesterol, P-CRP, and P-homocysteine. Non-normally distributed variables were log transformed before analysis. For P-NfL, 1 outlying sample (more than 10 SD higher than the mean) was identified, and statistical tests were performed with and without this individual as a sensitivity analysis. The analyses of the association between P-NfL and eGFR was repeated in the full H70 Birth Cohort of 1,151 individuals, with data on eGFR and P-NfL. Cross-sectional linear regression analysis was also performed with P-NfL as the independent continuous variable and eGFR as the dependent variable, adjusted for the same variables as in the logistic regression model. For longitudinal statistical analysis of the predictive value of P-NfL on incident CKD, a Cox proportional hazards model was used, adjusting for the same variables as in the other regression models. P-NfL divided by quartiles was used as a categorical variable in the Cox proportional hazards model. The proportional hazards assumption was tested through a hierarchical regression strategy, where each regression model was followed up by the addition of time-dependent interaction terms. No model was significantly improved through this addition. GraphPad Prism  was used for the plots and statistics therein, and SPSS  was used for all other statistical analyses.Categorical variables are presented as n (%) and continuous variables as median (interquartile range [IQR]) unless otherwise specified. Categorical variables were compared between groups with the χlinks.lww.com/WNL/C849) (n = 744). Seventy-six of the 744 individuals (10.2%) included in the study experienced CKD. Comparing participants with and without CKD, there were no statistically significant differences in sex distribution, age, and years of education , 744 individuals met the inclusion criteria for this study. The characteristics of the participants are provided in ducation . Considewith CKD .p = 0.2586), mean lateral ventricular volume , and total volume of white matter lesions (p = 0.0790) were comparable between participants with and without CKD. One participant with dementia presented very small volumetric measurements. Exclusion of the participant did not change statistical outcomes in a sensitivity analysis and was therefore kept in the sample. Correlation analysis of eGFR and these markers of neurodegeneration did not reveal any significant correlations .Measurements of mean cortical thickness (p = 0.2715), t-tau (p = 0.7404), p-tau (p = 0.9412), and NfL (p = 0.2869) in the same magnitude, comparing participants with or without CKD.CSF concentrations of several different markers of neurodegeneration were analyzed in the 313 participants who accepted CSF sampling. Of them, 26 (8.3%) had CKD. Both groups presented levels of CSF Aβ42/40 (p < 0.001) compared with participants without CKD  (p = 0.0016). As expected, in participants with CKD and CDR = 0, eGFR was lower than in those without CKD (p < 0.001). P-NfL levels were also higher in participants with normal cognitive function and CKD compared with those without CKD  (links.lww.com/WNL/C849).P-NfL increased with lower kidney function measured as eGFR . Stratif> 0.999) , while Phout CKD  (p < 0.0CDR = 0) . In a selinks.lww.com/WNL/C849). One individual without CKD presented with extreme levels of P-NfL, and the analyses were therefore repeated without this individual, showing slightly higher OR and similar p values (eTable 4). There was also a statistically significant association between P-NfL and eGFR, assessed using a linear regression models adjusted for the same confounders as the logistic regression , demonstrating a statistically significant association between P-NfL and CKD . Additiogression .Participants were re-examined for eGFR, 5.5 (5.3–6.1) years  after the first visit. A total of 558 individuals without CKD at baseline had re-examination data for eGFR  years, 48% males, 76 new cases of CKD). Participants were stratified into quartiles by P-NfL levels from low to high, and the predictive value of P-NfL levels on incident CKD was estimated through a Cox proportional hazards model. P-NfL levels in the highest quartile were found to be a significant predictor of incident CKD after adjustment for age, sex, education, hypertension, diabetes (model II) and additional adjustments for smoking, BMI, fasting plasma glucose, LDL cholesterol, CRP, and homocysteine (model III) . Howeverp = 0.003), Aβ42/40 , and Aβ42/p-tau  and with lower t-tau levels . There was no significant correlation with p-tau, although the R coefficient and p values were similar to the eGFR/t-tau association (R = −0.15 and p = 0.071). In Aβ-negative participants, no correlations were seen for eGFR with any CSF biomarker. By contrast, eGFR correlated with lower P-NfL levels in both Aβ-positive and Aβ-negative participants with a similar R coefficient  and p values (p < 0.001 for both correlations). The 5 participants with dementia and CSF data were excluded in a sensitivity analysis, without any significant influence on R coefficients or p values . The correlation between t-tau and eGFR changed from p = 0.048 to p = 0.070 resulting in a shift over the p value threshold of 0.05, while R coefficients were still similar (R = −0.16 to R = −0.15).Participants with available CSF data were stratified based on Aβ status, and correlation analyses between fluid biomarkers of neurodegeneration and eGFR were performed . In totaIn this study, we assessed several different markers of neurodegeneration in 744 individuals from a population-based cohort of 70-year-olds, in relation to the presence or absence of CKD. We found that P-NfL was higher in cognitively healthy individuals with CKD and presented similarly high levels as seen in participants with mild dementia. The association between CKD, eGFR, and P-NfL was still significant after adjustment for several confounding variables in a logistic regression model. P-NfL was an independent predictor of incident CKD in a Cox proportional hazards model. Furthermore, the linear regression coefficient for eGFR with P-NfL seemed steeper in participants with CKD compared with participants with normal kidney function. We found that CKD did not influence any MRI measurement of neurodegeneration, and no MRI variable correlated with eGFR. In a substudy including a smaller sample of 313 participants with CSF data, Alzheimer-related biomarkers only correlated with eGFR in Aβ42-positive participants after stratification for Aβ42 pathology.5-43 but because several risk factors and comorbidities are shared between the 2 conditions, it is difficult to determine the specific underlying mechanism. In this study, we did not observe any differences in structural MRI measurements between participants with or without CKD. Furthermore, we did not observe any difference in the established CSF biomarkers, between the 2 groups in the smaller sample of participants contributing with the CSF. The presence of CKD therefore did not seem to have any major confounding influence on CNS integrity in any aspect in this community-based sample. However, there was an association between P-NfL and both CKD and eGFR, indicating that kidney function is associated with some form of neurodegenerative pathology.19CKD has previously been associated with markers in Alzheimer pathology,45 Studies in patients with diabetes and in children with congenital CKD have discussed potential links to NfL released from the CNS,12 while a study of patients with end-stage renal disease did not find any correlation between P-NfL and cognitive function measured through Mini-Mental State Examination.46 Support for a causal influence of CKD on neurodegeneration in CNS is found in children with congenital CKD, where P-NfL is elevated and cognitive impairment can be observed, possibly through shared genetic drivers.5 By contrast, a recent study including patients from French memory clinics did not find any influence of CKD status on the predictive value of circulating NfL on incident dementia.47 This could be explained by differences in study design and participant characteristics because the study was conducted in a clinical sample of patients with memory symptoms and measured longitudinal outcomes on incident dementia. Furthermore, P-NfL is elevated in polyneuropathy, a condition often seen in patients with CKD.48 Other community-based studies have previously reported observations on the influence of comorbidities on plasma-based biomarkers and reported an association between P-NfL and CKD.19 We extended these observations with measurements in a large Scandinavian community-based sample selected by birth date and found an association between CKD, eGFR, and P-NfL, using logistic and linear regression models adjusted for somatic comorbidities including diabetes and hypertension. We also found that P-NfL is a predictor of incident CKD. Furthermore, using stratified linear regression analysis, we observed that the association between P-NfL and eGFR is mainly manifest in participants with CKD. This indicates that the integrity of P-NfL as a marker to rule out underlying neurodegeneration in a general population should not be confounded to any larger degree in individuals with normal kidney function. While there was an association between P-NfL and eGFR, the levels of eGFR were similar between individuals with and without dementia in the range >60 mL/min/1.73 m2, suggesting that eGFR per se may not be considered an indicator of underlying neurodegenerative disease.The association between P-NfL and eGFR has been reported in several independent studies previously, including cognitively healthy Mexican Americans, non-Hispanic Whites, and participants from the Mayo Clinic Study of Aging.21 It is also feasible for this purpose because it is a blood-based biomarker. Our observations of a similar elevation of P-NfL in individuals with CKD as in dementia indicate that P-NfL may not be useful for this purpose in individuals with CKD. Because our study is based on a community-based sample of older individuals, our participants are often found in the primary care setting.Memory impairment is sometimes caused by conditions that are not related to neurodegeneration for example, depression. It is therefore a medical challenge in primary care and in clinical interventions studies to segregate groups with these symptoms by underlying etiology. P-NfL has shown great promise in identifying individuals who present cognitive symptoms without any underlying neurodegenerative condition, providing support on which patients to refer to a memory clinic.49 However, we observed a correlation between Aβ42, t-tau, and eGFR specifically in participants with Aβ pathology. CKD has previously been proposed to increase the risk of AD through several mechanisms, including increased levels of uremic toxins, calcium metabolism, and an altered hemodynamic regulation.42 Noteworthy, studies consistently propose a causal direction where CKD increases the risk of AD.42 In fact, CKD is one of the strongest risk factors of dementia.50 Considering previous reports, our results indicate that even a moderate decline in kidney function is associated with elevated markers of AD pathology. By contrast, the correlation between P-NfL and eGFR was independent of Aβ pathology status, indicating that the mechanisms previously discussed for P-NfL are not shared with the correlations to AD pathology.We also measured CSF biomarkers in a smaller sample of individuals and did not find any influence of CKD status. While a previous study has shown that CSF NfL is associated with several other comorbidities, it does not seem to present any strong association with CKD.7 However, the similarity in size between NfL (68 kDa16) and albumin (67 kDa) indicates that clearance should mainly be altered in patients with albuminuria and not all patients with CKD because proteins of this size do not normally pass the glomeruli. Studies with arterio-venous samples close to the kidney could provide the answer to this question. Regarding other limitations, the number of participants with dementia is low in this population-based sample and the results are not directly transferrable to clinical settings of patients with dementia. Furthermore, we did not have information on participant status of peripheral neuropathy, which limits the possibility to determine the main contributor of NfL in plasma. However, because there was no correlation between CSF-NfL and eGFR, it is also possible the periphery significantly contributes to plasma concentrations of NfL. Our observations on the correlation between CSF markers specific for AD and eGFR in participants with Aβ pathology were made in a limited sample and should be replicated in larger studies. Nonetheless, previous studies have reported similar observations, indicating that this observation in a population-based sample is valid.There are some limitations to consider in this study. Almost all participants included in the study were born in Europe, and studies in other parts of the world may find different results due to variations in environment, life style, and genetics. This study does not provide any causal evidence regarding the association between NfL, CKD, and eGFR. In the longitudinal analysis, high P-NfL was associated with an increased risk of CKD. However, it should be considered that the Cox regression model was not significant after adjustment for baseline eGFR, and it is possible that the association found is mainly caused by a collinearity between eGFR and P-NfL. It is possible that the elevated levels of P-NfL are a consequence of impaired renal clearance, as proposed by others.Future longitudinal primary care studies are warranted to evaluate the added value of measuring P-NfL in detecting individuals with a higher specificity and predictive performance, which will be the basis for the modification of existing clinical practices. The precision of P-NfL as a predictor of neurodegeneration in individuals with CKD should also be determined in larger community-based and clinical studies. Although more studies are needed, it would be wise for clinicians to take CKD status into account when interpreting P-NfL measurements. The predictive role of P-NfL on incident CKD should also be validated in other settings because it could indicate that some neurodegenerative conditions may lead to an impaired renal function over time.In a community-based cohort of 70-year olds, P-NfL was associated with both prevalent and incident CKD, while CSF and/or imaging measures did not differ by CKD status. Participants with CKD and dementia presented similar levels of P-NfL, which should be considered when using P-NfL as a neurodegeneration biomarker. Our observed correlations between Aβ42 and eGFR could indicate an association between kidney function and AD.


The results of the study revealed that the tele-exercise intervention improved participants’ body mass index (BMI) (p < 0.001), waist circumference (p < 0.001), cardiorespiratory fitness  (p < 0.001) and muscle function (sit to stand (p < 0.01), sit ups (p < 0.001) and push-ups (p < 0.001)). Beneficial effects were also observed on perceived anxiety  (p < 0.001), post-traumatic stress disorder (PTSD) symptoms (PCL-C) (p < 0.01), self-reported fatigue (p < 0.001), quality of life (QoL) (p < 0.05) and physical (p < 0.05), cognitive (p < 0.01) and emotional (p < 0.05) functioning (EORTQ-QLQ-C30). Our findings suggest that common cancer- and treatment-related adverse effects on physical performance, mental health and the overall QoL can be ameliorated through tele-exercise training programs in BCa survivors.The number of breast cancer (BCa) survivors has been steadily increasing due to advances in anti-cancer treatments, though these individuals suffer from various cancer- and treatment-related long-term side effects. The present study aimed at investigating the effects of a home-based tele-exercise training intervention on physical- and mental health-associated parameters in BCa survivors. A total of 13 female BCa survivors (age: 58.31 ± 3.13 years, BMI: 25.68 ± 0.62 kg/m Breast cancer (BCa) is the most common type of cancer in females, and it is estimated that 1 in 8 women will be diagnosed with breast cancer at least once during their lifetime ,3. InterIt is noteworthy that the BCa diagnosis appears to have a long-term impact on survivors’ daily lives by affecting them both physically and emotionally and, thus, compromising their quality of life (QoL). Poor cardiometabolic health, sarcopenia, osteoporosis, reduced range of motion, chronic fatigue and pain are some of the adverse effects of common anti-cancer therapeutic strategies, including surgery, chemotherapy, radiation and hormonal therapy ,7. AdditHowever, over the last few years research evidence supports that health-promoting lifestyle interventions in breast cancer survivors have multiple positive effects on physiological and psychometric parameters ,11. In pAlthough tele-exercise is gaining momentum, available data on supervised distance exercise programs in BCa survivors is still limited and further research is needed to verify the physical and mental health benefits of tele-exercise to these patients. Thus, the aim of the present study was to determine the potential effects of a two-month home-based supervised tele-exercise program, containing both aerobic and resistance training, on physical performance, psychological parameters and QoL in BCa survivors.All participants, who voluntarily enrolled in the present longitudinal intervention study, were thoroughly informed about the experimental procedures and signed a written informed consent form that was approved by the Ethics Committee of the Medical School of the National and Kapodistrian University of Athens. All privacy law regulations were followed regarding data collection and handling.A total of 13 women BCa survivors, aged 58.31 ± 3.13 years, volunteered to participate in the study after the approval by their personal physician. The participants enrolled in the study according to the following inclusion criteria: they should have been diagnosed with breast cancer within the last 5 years (the average time after the completion of their last treatment was 2.94 ± 0.32 years), have no distant metastasis, have undergone mastectomy, and have completed chemotherapy and/or radiation therapy. In addition, they had to be free of severe cardiovascular, renal, pulmonary or psychiatric disease and to be able to understand and speak Greek. BCa survivors participated in a home-based group tele-exercise training program consisting of two sessions per week with each session lasting one hour and containing both aerobic and resistance exercises . The proThe tele-exercise training program lasted 2 months and re-assessment of physical performance and somatometric characteristics was carried out every 4 weeks. Moreover, participants self-evaluated their quality of life and perceived post-traumatic stress and anxiety at the beginning and after the completion of the training program. 2) = body mass (kg)/body height2 (m2). According to the World Health Organization (WHO), a BMI ranging from 18.5 kg/m2 to 24.9 kg/m2 represents a healthy body weight range, whereas if it exceeds the 25 kg/m2 or 30 kg/m2, the individual is considered overweight or obese, respectively [Participants were asked to stand barefoot with their backs against a height rod in order to measure their height, while an electronic precision balance was used to assess their body mass. Afterward, the body mass index (BMI) was determined [BMI  was utilized to assess BCa survivors’ aerobic capacity . PatientParticipants’ muscle function of various muscle groups of lower and upper extremities as well as of the abdominals was assessed in the BCa survivors before, during and after the completion of the tele-exercise training program, using three different muscle function assessment tests. Specifically, the “sit-to-stand test”, which measures how many times an individual with the arms crossed in front of the chest can sit and rise from a chair in 60 s, was used to evaluate muscle function of lower extremities . An armlQuality of life was self-reported by the BCa survivors, using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 , a widely used tool for the assessment of perceived QoL in cancer patients . This inThe Post-Traumatic Stress Disorder (PTSD) Checklist-Civilian version (PCL-C) was used to evaluate typical PTSD symptoms. It is composed of 17 self-reported questions based on the fourth revision of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) diagnostic criteria regarding PTSD. BCa survivors were instructed to answer carefully to what extent they experienced each symptom within the last month, rating the level of symptoms from one  to five (extremely). The total score represents the extent of PTSD symptomatology with the severity increasing as the total score rises. In general, a score greater than or equal to 50 is considered to reflect a full PTSD diagnosis . Anxiety was evaluated using the Zung Self-Rating Anxiety Scale (SAS) which is a 20-item tool with psychometric properties. Respondents should evaluate each item on a 4-point scale, grading from “rarely” to “always”, according to their individual perceived situation in the past week. In order to reduce the possibility of bias in the responses, while 15 items of the questionnaire contain negative claims regarding anxiety, the remaining five items convey positive statements. The total anxiety index is obtained by multiplying the sum of the score in each item by 1.25. Thus, the raw score ranges from 20 to 80; however, the final anxiety index lies between 25 and 100. Similar to the PCL-C assessment tool, a low index in the Zung scale signifies poor anxiety-related manifestations .t-test or a non-parametric Wilcoxon sing-ranked test was employed for the analysis of questionnaires’ scores at the two time points of evaluation depending on the normal or non-canonical distribution of the data, respectively. One-way analysis of variance (ANOVA) or the non-parametric alternative of Friedman test was utilized to examine the potential differences in the physiological and functional parameters before, during and after the intervention. No missing values occurred and the statistical significance was set at p < 0.05.Statistical analysis was performed using the Graphpad Prism statistical package . Mean and standard error of the mean (ΜΕAΝ ± SE) were used for descriptive statistics and Shapiro–Wilk test was performed to assess the normality of data distribution. A parametric paired p < 0.001), while no differences (p > 0.05) were found four weeks after the initiation of the training program  and to 541.54 ± 14.00 m after the completion of the eight-week training program . Changes in the evaluated cardiorespiratory fitness-related parameters of the participants because of the tele-exercise training program are presented in p < 0.01; p < 0.001) were also found regarding the core muscle function as indicated by the increased number of “Sit-Ups” repetitions at the fourth (18.85 ± 0.78 reps) and eigth (19.69 ± 0.72 reps) week of the training program, respectively, compared to baseline (14.92 ± 0.56 reps) (p < 0.05) and 11.21 ± 0.55 reps after eight weeks (p < 0.001) of tele-exercise training  b. Similatraining c.p < 0.05). Similar improvements were also self-reported regarding the scores of “Physical Functioning” , “Cognitive Functioning”  and “Emotional Functioning”  as a result of the exercise training intervention. Social and role functioning scores exhibited a tendency to increase (improve) without reaching statistical significance (p > 0.05). Furthermore, regarding the long-term cancer- and treatment-related symptoms, the perceived fatigue was scored by 60.68 ± 8.40 at baseline and decreased to 26.49 ± 4.63 after the two-month exercise training (p < 0.001). Pain was also decreased to 16.67 ± 5.66 compared to baseline values (26.92 ± 6.94), though these changes were not statistically significant (p > 0.05). BCa survivors filled in the EORTC-QLQ-C30 questionnaire to self-evaluate various QoL-associated parameters at the beginning and the end of the tele-exercise training program . It was p < 0.01) even in the survivor who had a PTSD diagnosis at baseline (score: 20). Furthermore, the tele-exercise training program induced a significant reduction in the BCa survivors’ anxiety index  in contradistinction to most of the participants (score: 37.15 ± 3.29). Overall, the PTSD symptoms were decreased after the eight-week exercise intervention (score: 24.38 ± 2.01, The present study aimed at investigating the effect of a home-based supervised tele-exercise training program on physical- and mental health-associated variables in BCa survivors. Our findings suggest that a two-month tele-exercise training, consisting of aerobic, resistance and flexibility exercises, was adequate and effective in improving somatometric characteristics, physical performance, psychological parameters, such as anxiety and PTSD, and eventually overall QoL in BCa survivors. Specifically, the indirect indicators of body composition, BMI and waist circumference, were improved significantly after the eight-week exercise intervention. Similar results have been reported in previous remote or supervised in-person exercise programs including both aerobic and resistance training in BCa survivors ,36. Moreover, BCa survivors’ cardiorespiratory fitness was enhanced through the tele-exercise training, as it was indicated by the advances in 6MWT performance and the improvements in the perceived exertion-related variables, dyspnea and leg fatigue at the end of this submaximal exercise test. Although recent studies using home-based exercise interventions lasted 3 or 4 months and confirmed that remote exercise interventions could positively impact cardiorespiratory health of cancer survivors ,37, to tFurthermore, muscle function assessment in various muscle groups showed significant improvements during the two-month exercise program in the BCa survivors. These results are in agreement with findings of previous studies where distance exercise interventions were delivered in various oncology patients either synchronously or asynchronously ,42. Engagement in physical activity programs has been suggested to improve overall functional ability and QoL and ameliorate anxiety and PTSD symptoms in cancer survivors ,38,43,44Overall, this study showed that tele-exercise was well tolerated by all the BCa survivors and their compliance to the remote exercise training program was not compromised, highlighting the feasibility of distance-supervised exercise programs in this clinical population. Moreover, the various physical and mental health benefits gained even after a shorter training period underline the efficacy and effectiveness of such programs in improving the overall QoL of BCa survivors. These findings suggest that cancer survivors should be strongly advised to participate in exercise programs, while the utilization of advanced digital technology, such as video call applications or recorded video sharing platforms, can efficiently support the access of those people to regular exercise when physical presence is not possible. However, the absence of a control group and the relatively small sample size are limitations of the present study that could lead to an underestimation of the health benefits of tele-exercise training for breast cancer survivors. Furthermore, such exercise interventions with longer durations ,37 or coThe present study demonstrated that a remotely supervised exercise training program can be a feasible and effective intervention for breast cancer survivors, offering them various physical performance, mental health and QoL benefits. Nevertheless, increasing the motivation of cancer survivors to be involved in tele-exercise programs and their familiarization with video calls and other advanced technologies are emerging issues that should be addressed, in order this form of exercise intervention to be utilized for overcoming distance barriers. Moreover, this strategy could, in turn, not only increase exercise adherence but also enable a greater number of survivors to participate in physical activity programs as part of healthy lifestyle modifications for them. Furthermore, this exercise intervention could be utilized in the more aggressive phases of anti-cancer treatment when access to training facilities may be challenging, or isolation is preferred.


Multivariable analysis models for eGFR outcome improved after the addition of these biomarker levels. Several donor, recipient and transplantation factors significantly affected the baseline of urinary biomarkers. In conclusion, urinary biomarkers are of added value for the prediction of graft outcome, but influencing factors such as the timing of measurement and transplantation factors need to be considered.Early non-invasive detection and prediction of graft function after kidney transplantation is essential since interventions might prevent further deterioration. The aim of this study was to analyze the dynamics and predictive value of four urinary biomarkers: kidney injury molecule-1 (KIM-1), heart-type fatty acid binding protein (H-FABP), N-acetyl-β-D-glucosaminidase (NAG), and neutrophil gelatinase-associated lipocalin (NGAL) in a living donor kidney transplantation (LDKT) cohort. Biomarkers were measured up to 9 days after the transplantation of 57 recipients participating in the VAPOR-1 trial. Dynamics of KIM-1, NAG, NGAL, and H-FABP significantly changed over the course of 9 days after transplantation. KIM-1 at day 1 and NAG at day 2 after transplantation were significant predictors for the estimated glomerular filtration rate (eGFR) at various timepoints after transplantation with a positive estimate ( During the procedure of organ donation and transplantation, several potentially harmful processes occur, affecting the viability and quality of the kidney graft. Ischemia reperfusion injury (IRI) is inevitable and additional injury like brain death induced inflammation in the case of donation after brain death (DBD) donors, or prolonged warm ischemia in the case of donation after circulatory death (DCD) donors, may further harm the graft ,2,3. ThiRegarding kidney injury and graft outcome, several urinary biomarkers have been suggested including kidney injury molecule-1 (KIM-1), heart-type fatty acid binding protein (H-FABP), N-acetyl-β-D-glucosaminidase (NAG), and neutrophil gelatinase-associated Lipocalin (NGAL). These four biomarkers are upregulated, excreted, and/or released by the kidney at the time of injury like IRI, and could therefore be a proxy of the severity of damage . These fThe baseline characteristics of the donors and recipients are summarized in p < 0.001), followed by significant increases until day 2 (p < 0.001). Afterward, the KIM-1 levels decreased from day 2 until day 6 after transplantation (p < 0.001). The levels of NGAL significantly decreased after transplantation. We observed a significant decrease between 2 h and day 1 (p < 0.001), day 2 (p = 0.007) and day 6 (p < 0.001). The NAG levels showed a significant decrease between the first urine and day 1 after transplantation (p < 0.001), followed by a significant increase at day 2 (p < 0.001). The significant increase continued between day 6 and day 9 after transplantation (p = 0.043). Similar to NGAL, the levels of H-FABP decreased over 9 days. The H-FABP levels significantly decreased between first urine until day 1 after transplantation (p < 0.001), which continued between day 1 and day 2 (p = 0.002), and day 2 and day 9 (p < 0.001).The dynamics of the urinary biomarkers are presented in p < 0.001) and the addition of patient ID as a random effect improved the models. The best-fitting models are presented in p = 0.0065) and with every min increase of second warm ischemia time ), but the univariable model for sex mismatch fitted the data best. Presence of a sex mismatch and an unrelated donor significantly increased the intercept . Every year increase in the recipient age significantly increased the baseline of NAG activity with 0.0079 IU/mmol in a univariable model (p = 0.0213). The best-fitting model was represented by the addition of the sex mismatch. The baseline of the H-FABP model increased significantly by every minute increase of the cold ischemia time with 0.0065 ng/mmol . The multivariable mixed models did not perform superior to the univariable mixed models.In all models, time had a significant effect on the course of the urinary biomarkers (p = 0.010), 3-month (p = 0.034), 6-month (p = 0.025), 12-month (p = 0.008), and 24-month eGFR (p = 0.025). The NAG levels on day 1 were significant negative predictors for 1-month, (p = 0.017), 6-month (p = 0.006) and 24-month eGFR (p = 0.037). However, NAG on day 2 was a positive predictor for 6-month (p = 0.020) and 12-month eGFR (p = 0.022). NGAL on day 1 was a significant negative predictor for 1-month eGFR (p = 0.004). H-FBAP was not a significant predictor for the eGFR measurements. Changes between the first and last sample moment of all biomarkers were also implemented in regression models but did not show significant predictive value for renal outcome.Univariable analysis of all the urinary biomarkers indicated several significant predictors for eGFR after transplantation, which are shown in p = 0.018), 3-month (p = 0.014), 6-month (p = 0.007), 12-month (p = 0.004), and 24 month eGFR (p = 0.016). The addition of NAG at day 1 and day 2 after transplantation improved the prediction model for 6-month eGFR . NAG 2 days after transplantation was also a significant predictor for 12-month eGFR (p = 0.013). The levels of NGAL at day 1 after transplantation improved the prediction model for 1-month eGFR (p = 0.003).All significant predictors from the univariable regression analysis were implemented in a multivariable regression model, as shown in This post-hoc analysis shows that the levels of KIM-1, NAG, NGAL, and H-FABP significantly changed over the course of nine days after transplantation in our LDKT cohort, showing varied dynamic patterns. The patient, recipient, and transplantation characteristics explained the variability in the baseline between subjects. In addition, the predictive qualities differed per biomarker and between timepoints ranging from positive to negative prediction. This indicates that the timing and context of biomarker measurements are important when using these markers as an outcome measure in kidney injury research, since classically marked injury biomarkers may be involved in injury as well as repair mechanisms.Our results are conflicting with known animal experiments and clinical trials, as we demonstrated a positive prediction of graft function with KIM-1 levels at day 1 after transplantation. KIM-1 is mainly viewed as a marker of kidney injury. Regarding kidney transplantation, most research evaluating KIM-1 has been performed in the recipients of deceased donor kidneys and showed an association of KIM-1 with suboptimal outcomes ,19,20. MIn contrast to KIM-1, NAG is a more disputable predictor with equivocal results. Urinary NAG activity at day 1 is a negative predictor for eGFR from 1 up to 24 months after transplantation. This is in line with previous research ,33,34,35In line with previous studies, NGAL was a negative predictor for outcome after transplantation outcome ,36,37,38In this study, we demonstrated that the levels of H-FABP were the highest in the first produced urine after transplantation, followed by a significant decrease over time. Similarly, plasma H-FABP was found to be elevated after kidney transplantation and similar to our results, peaked immediately after reperfusion [17. A study by Schaub et al. demonstrated that the H-FABP levels, measured pre-operatively and up to three days post-operatively, were related to the development of AKI following cardiac surgery . HoweverInterestingly, the presence of a sex mismatch between the donor and recipient significantly increased the baseline of the multiple biomarker models. Several studies have shown that a sex mismatch has an impact on the graft. In a cohort of simultaneous pancreas–kidney transplantation, Coffman et al. demonstrated that organs derived from male donors had significantly higher graft survival rates compared to female donors . To our n = 3). We therefore were not able to look at the association of the biomarker levels and graft dysfunction in terms of DGF. Therefore, further research is needed to determine the predictive value of these biomarkers on adverse graft outcomes in a larger study population. Another important limitation is the challenge in predicting the outcome after transplantation in the LDKT recipients. Fortunately, complications after transplantation were limited in number and graft function was relatively good. However, it may be beneficial to establish appropriate models for the prediction of short- and long-term graft outcome since not all recipients had a eGFR >50 mL/min/1.73 m2 after two years and acute rejection occurred in 16% of our study population. Furthermore, we needed to acknowledge the lack of multiple testing correction. This was an exploratory study, and we considered the analysis of every biomarker per timepoint with five repetitive eGFR measurements not to be a substantial risk for false positives. The fact that we sequentially measured the urinary biomarker levels is a major strength, which provides insight into the temporal character of urinary biomarkers in LDKT and the possible timeframes in which urinary biomarkers can be used as a biomarker. In addition, the fact that we used splint urine ensures that the biomarkers measured originate from the transplanted kidney only.A few limitations of this study must be addressed. Our results only suggest associations and do not necessarily imply causality between the urinary biomarkers and eGFR levels or graft outcome. In addition, our sample size of 57 LDKT recipients was small and complications after transplantation like DGF were rare  trial, a prospective randomized controlled trial on the effect of two different anesthetic agents (propofol vs. sevoflurane) on renal outcome in LDKT. The VAPOR-1 trial was approved by the local Institutional Review Board (METc 2009/334), registered with ClinicalTrials.gov (NCT01248871) and conducted at the University Medical Center of Groningen between September 2010 and October 2014. Details of the study have previously been published . A totalThe primary outcome was to study the release of four urinary biomarkers: KIM-1, NGAL, NAG, and HFABP in the period after transplantation. These biomarkers were chosen as they either represent different injury mechanisms or have a different origin in the kidney. Secondary outcomes were predictive values of urinary biomarkers to eGFR, the occurrence of DGF, acute rejection episodes, graft loss, and patient mortality. In recipients, eGFR was calculated with the use of the CKD-EPI formula at month 1-, 3-, 6-, 12-, and 24-months after transplantation.Urine samples were taken at standardized time points. Sample points in recipients were first urine produced upon reperfusion, 2 h post-operative and on days 1, 2, 6, and 9 after transplantation. Urinary samples were collected from a splint (representing urine solely from the transplanted kidney). H-FABP was not measured on day 6. Timepoints are depicted in The urinary KIM-1, NGAL, and H-FABP levels were measured with the duoset enzyme-linked immunosorbent assay . NAG was measured by the modified enzyme assay using p-nitrophenyl-N-acetyl-β-D-glucosaminidase as the substrate. Urinary creatinine was determined on a Roche Modular chemistry analyzer . KIM-1, H-FABP, and NAG were measured for the VAPOR-1 study. For this post-hoc analysis, we additionally measured NGAL.p-value ≤ 0.05 for all comparisons.Statistical analysis was performed in SPSS version 28 , GraphPad Prism version 8.0.1. , and R Studio . It was tested whether the continuous variables followed a normal distribution with the use of the Shapiro–Wilk normality test and visualization by the normal probability (Q–Q) plots. Data were corrected for extreme outliers (>2 SD). Descriptive statistics were presented as the mean (±SD) for the normally distributed variables, median (interquartile range (IQR)) in the case of non-normal distributions, or proportions n with corresponding percentages (%) for the categorical variables. Before statistical testing, we log transformed the urinary biomarker to better approximate a normal distribution. Statistical significance was set at a T-test or Wilcoxon signed rank test was performed. Linear mixed-effects models were used to characterize and explain the variability of the urinary biomarkers over time, where time was entered as a fixed effect. The time effect was evaluated assuming a linear relationship, but nonlinear trends were also evaluated using polynomial functions. Estimates of the covariates are presented as b with standard error (SE). Patient identification was entered as a random effect. Donor, recipient, and transplantation characteristics (based on literature) were evaluated on the fixed effects, representing the baseline and parameters describing changes over time, on their ability to explain the variability in urinary markers. Combinations of significant variables in the univariable models were tested in the multivariable models to study whether a combination of characteristics resulted in additional explanation of the variability in the biomarkers. The best-fitted models are presented based on the Akaike information criteria (AIC) and significance of the model parameters.First, we analyzed the dynamics and the variability between the subjects of the urinary biomarkers. For the dependent variables, a paired Next, we evaluated the predictive value of the urinary biomarkers for the transplantation outcomes. Univariable linear regression analyses were performed to analyze the urinary biomarkers as predictive variables in relation to the renal outcome parameters. Significant predictive variables in the univariable models were added to a multivariable regression model to assess the improvement in the prediction, based on the adjusted R-square.